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In response to the challenges posed by the conventional manual flange docking method in the LNG (Liquefied Natural Gas) loading process, such as low positioning accuracy, constraints on production efficiency and safety hazards, this study analyzed the LNG five-axis loading arm’s main functions and structural characteristics.

An automated solution for the joints of the LNG loading arm was designed. The forward kinematic model of the LNG loading arm was established using the Denavit–Hartenberg (D-H) parameter method, and its workspace was analyzed. The Newton–Raphson iteration method was employed to solve the inverse kinematics of the LNG loading arm, facilitating trajectory planning. The relationship between the target position and the joint variables was established to verify the stability of the arm’s motion. Flange center identification was achieved using the Hough transform function. Based on the ROS platform, combined with Gazebo and Rviz, an experimental simulation of automatic docking of the LNG loading arm was conducted.

The docking errors in the XYZ directions were all less than 0.8 mm, meeting the required docking accuracy. Moreover, the motion performance of the loading arm during docking was smooth and free of abrupt changes, validating its capability to accomplish the automatic docking task.

The proposed trajectory planning and automatic docking scheme can be used for the rapid filling of LNG filling arms and LNG tankers to improve the efficiency of LNG transportation. In guiding the docking, the proposed automatic docking scheme is an accurate and efficient way to improve safety.

Traditional robot arm trajectory planning methods have problems such as insufficient generalization performance and low adaptability. This paper aims to propose a method to plan the robot arm’s trajectory using the trajectory learning and generalization characteristics of dynamic motion primitives (DMPs).

This study aligns multiple demonstration motion primitives using dynamic time warping; use the Gaussian mixture model and Gaussian mixture regression methods to obtain the ideal primitive trajectory actions. By establishing a system model that improves DMPs, the parameters of the nonlinear function are learned based on the ideal primitive trajectory actions of the robotic arm, and the robotic arm motion trajectory is reproduced and generalized.

Experiments have proven that the robot arm motion trajectory learned by the method proposed in this article can not only learn to generalize and demonstrate the movement trend of the primitive trajectory, but also can better generate ideal motion trajectories and avoid obstacles when there are obstacles. The maximum Euclidean distance between the generated trajectory and the demonstration primitive trajectory is reduced by 29.9%, and the average Euclidean distance is reduced by 54.2%. This illustrates the feasibility of this method for robot arm trajectory planning.

It provides a new method for the trajectory planning of robotic arms in unstructured environments while improving the adaptability and generalization performance of robotic arms in trajectory planning.

The paper argues for the introduction of pedagogies of optimism (and implicitly of hope) in schools as a response to the danger of pessimism, skepticism and helplessness characterizing periods of armed conflicts.

A conceptual analysis.

Following an analysis of armed conflicts and their impact on educational systems, the critical contribution of pedagogies of optimism is illuminated. Teachers are encouraged to follow major phases in this kind of pedagogy, such as discovery, acceptance of the situation, imagination and critical thinking.

Practical suggestions are provided at the end of the paper.

This chapter explores the nature of military law and IHL during the cold war period. It explores what treaties were completed, Additional Protocols I and II of the 1949 Geneva Conventions, the ad hoc international tribunals of the 1990s and 2000s, and examines the ICJ’s ruling of the legality of nuclear weapons.

This chapter examines the explosion in International Humanitarian Law between the US Civil War and World War I. The primary foci are the Hague Conventions on land warfare and the Geneva Conventions for the sick and wounded. This body of treaties is the foundation of IHL and the modern laws of war. Most of central issues in the international laws of war emerge in this period.

It is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.

The autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.

The estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.

Up to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

To setup a theoretical model for grasping cutting pieces of garment better, which will help to design a special soft gripper and push forward the automated level of garment manufacturing.

This paper first analyzed the mechanics of the grasping process and concluded the main factors that affect the success of grasping. A theoretical model named grasping fabric model (GFM) was constructed to show the mechanical relationship between the soft gripper and the fabric pieces. Subsequently, two fabric samples were selected and tested for their friction properties and critical buckling force, and the test data were substituted into the theoretical model GFM to obtain the grasping parameters required for fabric grasping layer by layer.

It was found that (1) the critical buckling force of the fabric is mainly influenced by the bending stiffness and the deformation length of the fabric during grab. (2) The difference between the friction between the soft gripper and the fabric and the friction between the fabric, that is DF1-2, has an important influence on the accuracy of grasping layer-by-layer.

It showed that the grasping parameters provided by GFM enable the two samples to be more effectively separated layer by layer, which verifies that the GFM model is strong enough for the possible application in garment automated production.

This chapter focuses on the US Civil War of 1861–1864, the application of the laws of war to a civil war, and gives great attention to US Army General Order 100 (aka The Lieber Code), the first set of laws to direct and constrain the behavior of troops in the field.